Introduction: With increasing availability of pathogen genetic and especially whole-genome sequence data, there is a pressing need for analytical tools and innovative approaches to make use of them. In particular, methods for using genomic data to make inferences about transmission chains and pathogen evolution under selection by host immunity, vaccines, and antibiotics, are still in their infancy. These questions are fundamentally different from the types of questions asked when examining one sequence at a time, which illuminate the biology of conserved aspects of infection and pathogenesis. Population genomic studies shed light on population heterogeneity in the pathogen, its consequences and causes. These inferences naturally lend themselves to the estimation of parameters for transmission-dynamic models and, even more fundamentally, to the determination of how such models should be structured, and the testing of their predictions. To date, using MIDAS and non-MIDAS funding for analytic efforts, and non-MIDAS funding for the costs of sequencing, we have made a number of significant discoveries over the last five years using pathogen population genomics and genetics, and we have identified many opportunities to improve and expand methods over the next five years, as well as to apply existing methods to significant questions of biology and epidemiology.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54GM088558-10
Application #
9544980
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2018-09-01
Budget End
2019-08-31
Support Year
10
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Harvard University
Department
Type
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
Moser, Carlee B; White, Laura F (2018) Estimating age-specific reproductive numbers-A comparison of methods. Stat Methods Med Res 27:2050-2059
Zimmer, Christoph; Leuba, Sequoia I; Cohen, Ted et al. (2018) Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models. Stat Methods Med Res :962280218805780
Olesen, Scott W; Grad, Yonatan H (2018) Racial/Ethnic Disparities in Antimicrobial Drug Use, United States, 2014-2015. Emerg Infect Dis 24:2126-2128
Li, Yu; Chang, Zhaorui; Wu, Peng et al. (2018) Emerging Enteroviruses Causing Hand, Foot and Mouth Disease, China, 2010-2016. Emerg Infect Dis 24:1902-1906
Wesolowski, Amy; Winter, Amy; Tatem, Andrew J et al. (2018) Measles outbreak risk in Pakistan: exploring the potential of combining vaccination coverage and incidence data with novel data-streams to strengthen control. Epidemiol Infect 146:1575-1583
Goldstein, Edward; Nguyen, Hieu H; Liu, Patrick et al. (2018) On the Relative Role of Different Age Groups During Epidemics Associated With Respiratory Syncytial Virus. J Infect Dis 217:238-244
Lam, Ha Minh; Wesolowski, Amy; Hung, Nguyen Thanh et al. (2018) Nonannual seasonality of influenza-like illness in a tropical urban setting. Influenza Other Respir Viruses 12:742-754
Yang, Juan; Lau, Yiu Chung; Wu, Peng et al. (2018) Variation in Influenza B Virus Epidemiology by Lineage, China. Emerg Infect Dis 24:1536-1540
Kahn, Rebecca; Hitchings, Matt; Bellan, Steven et al. (2018) Impact of stochastically generated heterogeneity in hazard rates on individually randomized vaccine efficacy trials. Clin Trials 15:207-211
Hitchings, Matt D T; Lipsitch, Marc; Wang, Rui et al. (2018) Competing Effects Of Indirect Protection And Clustering On The Power Of Cluster-Randomized Controlled Vaccine Trials. Am J Epidemiol :

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